NodeNode / Other

Convolution Layer

This node adds a Convolutional layer to the Deep Learning Model supplied by the input port. The layer performs convolution of the inputs (usually images) using a user defined number of convolution kernels.

Input ports
  1. Deep Learning Model Type: DL4J Model
    The model which will be extended by this layer.
Output ports
  1. Deep Learning Model Type: DL4J Model
    The model from the input port additionally containing this layer.
  1. Celebrity Recognition Using AlexNet
    deeplearning machine learning classification +3
    This workflow shows an example of image classification of celebrity faces using AlexNet. Note: Due to the size of the n…
    knime > Examples > 04_Analytics > 14_Deep_Learning > 01_DL4J > 13_Celebrity_Detection_Using_Alex_Net
  2. Classifying handwritten digits using KNIME, DL4J and a LeNet variant
    deep learning GPU image classification +2
    The workflow downloads, uncompresses and preprocesses the original MNIST dataset. The two "Normalize Images" components…
    knime > Examples > 04_Analytics > 14_Deep_Learning > 01_DL4J > 14_DeepLearningTutorial_MNIST > 01_Using_DeepLearning4J_to_classify_MNIST_Digits
  3. Example of a simple Convolutional Network
    deeplearning machine learning classification +2
    This workflow shows how to create a simple convolutional network and use it for image classification.
    knime > Examples > 04_Analytics > 14_Deep_Learning > 01_DL4J > 05_Network_Example_Of_A_Simple_Convolutional_Net
  4. Font Detection Using A Convolutional Net
    deeplearning machine learning classification +2
    This workflow shows an example of how to detect the fonts of letters using a convolutional network. Credits to: Kevin M…
    knime > Examples > 04_Analytics > 14_Deep_Learning > 01_DL4J > 12_Font_Detection_Using_A_Convolutional_Net
  5. Basic Concepts of Deeplearning4J Integration
    deeplearning machine learning neural networks
    This workflow shows basic concepts of the KNIME Deeplearning4J Integration.
    knime > Examples > 04_Analytics > 14_Deep_Learning > 01_DL4J > 01_Basic_Concepts_Of_Deeplearning4J_Integration
  6. Simple Anomaly Detection Using a Convolutional Network
    deeplearning machine learning anomaly detection +2
    This workflow shows how to do anomaly detection of the MNIST dataset using a convolutional network. Workflow Requiremen…
    knime > Examples > 04_Analytics > 14_Deep_Learning > 01_DL4J > 09_Simple_Anomaly_Detection_Using_A_Convolutional_Net